A large shared computing platform is usually divided into several virtual
clusters of fixed sizes, and each virtual cluster is used by a team. A cluster
scheduler dynamically allocates physical servers to the virtual clusters
depending on their sizes and current job demands. In this paper, we show that
current cluster schedulers, which optimize for instantaneous fairness, cause
performance inconsistency among the virtual clusters: Virtual clusters with
similar loads see very different performance characteristics.

We identify this problem by studying a production trace obtained from a large
cluster and performing a simulation study. Our results demonstrate that when
using an instantaneous-fairness scheduler, a large VC that contributes more
resources during underload periods can not be properly rewarded during its
overload periods. These results suggest that not using resource sharing history
is the root cause for the performance inconsistency.